Dear researchers, we cordially invite you to our symposium, where esteemed specialists from the field will be present as speakers.

S1. Cybersecurity

S1.1. Software Security
S1.2. Security Threats and Vulnerabilities
S1.3. Computer Network Security
S1.4. Industrial Control Systems (ICS) Security
S1.5. SCADA Security
S1.6. Security in Mobile and Wireless Networks
S1.7. Mobile Applications and Security
S1.8. Mobile Smart Phone and Tablet Security
S1.9. Cryptographic Algorithms
S1.10. High Performance Cryptography
S1.11. Web/Internet Security
S1.12. Reverse Engineering
S1.13. Cyber Security Trends
S1.14. Cloud Computing and Security
S1.15. Deep Understanding of and Practical Skills in Software Security

S2. Metaverse

S2.1. Machine Learning and data analytics in the metaverse
S2.2. Metaverse platform security and audit ability
S2.3. Metaverse system and architecture
S2.4. Metaverse architecture: Centralized vs. decentralized
S2.5. Blockchain and the metaverse
S2.6. Metaverse data management and analysis
S2.7. Digital real estate, assets, and the economy of Metaverse
S2.8. Governance models for the Metaverse
S2.9. Policy implications and regulatory frameworks
S2.10. Smart transportation system and technology in Metaverse
S2.11. Smart healthcare service monitoring in Metaverse
S2.12. Smart city and urban computing in Metaverse
S2.13. Smart education in metaverse
S2.14. Smart Museum in metaverse
S2.15. Games in Metaverse
S2.16. Metaverse virtual economy

S3. Artificial Intelligence

S3.1. Data Science and Business Intelligence
S3.2. Social Network Analysis Methods and Applications
S3.3. Visualization and Data Mining
S3.4. Business Intelligence and Data Mining
S3.5. Decision Support Systems
S3.6. Cloud Computing
S3.7. Augmented Reality
S3.8. Big Data
S3.9. Deep Learning
S3.10. High Performance Computing
S3.11. Autonomous Vehicles
S3.12. Robotics and Automation
S3.13. Computer Vision and Pattern Recognition
S3.14. Facial Recognition and Expression Detection
S3.15. Speech & Pattern Recognition
S3.16. Artificial Intelligence and Machine Learning at Scale
S3.17. Machine Learning on GPUs, TPUs, CPUs
S3.18. Explainable Artificial Intelligence
S3.19. Natural Language Processing (NLP)
S3.20. Ethics in Artificial Intelligence

S4. Software Engineering

S4.1. Software Architectures, Service-oriented Architectures
S4.2. Model-driven Internet of Things
S4.3. Model-driven Software Engineering
S4.4. Domain-specific Language Engineering
S4.5. Collaborative Software Development and Modeling
S4.6. Component-based Software Engineering and Development
S4.7. Software Maintenance, Migration and Modernization
S4.8. Project Management in Software Development
S4.9. Semantic Web: Concepts, Technologies and Applications
S4.10. Advanced database and Web Applications
S4.11. Load Balancing and Sharing
S4.12. Cluster and Grid Computing
S4.13. Peer-to-Peer Architectures and Networks
S4.14. Machine Learning on GPUs, TPUs, CPUs
S4.15. Partitioning, Mapping, and Scheduling
S4.16. Benchmarking and Performance Assessment in High Performance Computing
S4.17. Open Source Tools for Artificial Intelligence
S4.18. High Performance Interconnection Networks
S4.19. Fault Tolerance and Resilience in High Performance Computing Systems
S4.20. Gamification